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Record W2339186586 · doi:10.1149/06801.1455ecst

Nickel Doped Lanthanum Chromite Perovskite: A Novel Regenerable Anode Material for Solid Oxide Fuel Cells

2015· article· en· W2339186586 on OpenAlexaff
Yifei Sun, Meng-Ni Wang, Jing‐Li Luo

Bibliographic record

VenueECS Transactions · 2015
Typearticle
Languageen
FieldMaterials Science
TopicAdvancements in Solid Oxide Fuel Cells
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMaterials scienceLanthanumPerovskite (structure)NickelNickel oxideOrthorhombic crystal systemThermogravimetric analysisAnodeNon-blocking I/OScanning electron microscopeChemical engineeringAnalytical Chemistry (journal)Inorganic chemistryMetallurgyComposite materialCrystal structureChemistryElectrodeCrystallographyCatalysis

Abstract

fetched live from OpenAlex

A series of nickel doped lanthanum strontium chromite (La 0.7 Sr 0.3 Cr 1-x Ni x O 3-y, x=0.05-0.3) perovskite anodes for SOFCs was fabricated by glycine combustion method. The structural properties and electrochemical performances of the anode materials were investigated. It was found that the materials with various nickel dopant contents showed an orthorhombic perovskite phase. However the formation of parasitic phase of NiO could also be detected for the material with nickel content >20%. Thermogravimetric analysis (TGA) measurement performed in 5% H 2 -N 2 showed that the mobility of oxygen in the materials increased with the increase of Ni content. For La 0.7 Sr 0.3 Cr 0.8 Ni 0.2 (LSCNi) sample, Scan Electron Microscope (SEM) images detected the in-situ growth of nano Ni particles with the average diameter of 20 nm anchoring on surface of the material after the exposure in reducing atmosphere. The material with exsolution of Ni nano particle displayed improved power density output and reduced the activation polarization resistance compared to pure La 0.7 Sr 0.3 CrO 3-y (LSC).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.474
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.036
GPT teacher head0.286
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueECS TransactionsSame topicAdvancements in Solid Oxide Fuel CellsFrench-language works237,207